Battery Ageing Interval Prediction for Maximum Service Duration
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Solution Overview
Problem
Existing methods for predicting the remaining life of batteries, especially in complex and varied operating conditions, are not sufficiently reliable or precise, leading to suboptimal maintenance intervals and potential battery failures.
Innovation Solution
A method that selects a battery usage period, obtains degradation factor values, determines aging indicators, identifies variation intervals of these factors, and uses a predictive model to estimate the limit duration of use based on operational limits, ensuring precise and reliable estimation of battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional battery life prediction methods based on number of cycles are used, then the prediction process is simple, but the prediction reliability is insufficient for complex and varied operating conditions
Solution Approach 1:
The patent transforms the prediction approach from using a single parameter (number of cycles) to using multiple degradation factors (temperature, voltage, current, time) with different weights. This parameter change enables reliable prediction under varied operating conditions by capturing the complex interactions between different stressors on the battery.
Solution Approach 2:
The patent segments the battery degradation process into multiple independent degradation factors, each representing a specific stressor (temperature, voltage, current, time). By segmenting the overall degradation into these components, the system can analyze and weight each factor separately, improving prediction reliability while maintaining manageable complexity through modular processing.
2Reliability
If frequent maintenance operations are performed, then battery reliability is maintained, but productivity decreases due to increased human intervention and downtime
Solution Approach 1:
The patent performs preliminary action by predicting battery remaining life and degradation trends before actual failure occurs. This advance prediction allows maintenance to be scheduled optimally - not too early (which would reduce productivity) and not too late (which would compromise reliability). The system proactively identifies when maintenance will be needed based on real-time degradation monitoring.
Solution Approach 2:
The patent implements continuous feedback by monitoring degradation factors in real-time and updating the remaining life prediction accordingly. This feedback loop allows the system to adjust maintenance scheduling dynamically based on actual battery condition rather than following fixed schedules, thereby optimizing both reliability and productivity by performing maintenance only when truly necessary.
3Productivity
If battery usage period is extended beyond predicted limits, then productivity increases, but the risk of battery failure increases
Solution Approach 1:
The patent uses continuous feedback from real-time monitoring of degradation factors to dynamically adjust the predicted remaining life. This feedback mechanism allows the system to extend operational limits safely by confirming the battery is still within acceptable degradation thresholds, or to alert operators to reduce usage when approaching failure risk thresholds, thereby optimizing the balance between productivity and reliability.
Data Source
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AI summary
The invention relates to a method for determining a maximum duration of use of a battery, said method comprising: a step of selecting a period (P) of use of the battery; a step of obtaining values of factors of degradation (Fi) of the battery during the period of use of the battery selected during the selection step; a step of determining at least one indicator of ageing (ΔC, ΔR) of the battery on the basis of the degradation factor values obtained in the step of obtaining said values; and a step of identifying intervals (Fi , max/min) of variation of the degradation factors during said period of use, each ageing indicator being associated with actual variation intervals which each have a minimum value and a maximum value of said factors used during the determination step; and a step of predicting the maximum duration of use (D) on the basis of the variation intervals obtained in the step of identification, the at least one ageing indicator and the operating limits of the battery.